• DocumentCode
    715097
  • Title

    A decision tree based approach for microgrid islanding detection

  • Author

    Azim, Riyasat ; Yongli Zhu ; Saleem, Hira Amna ; Kai Sun ; Fangxing Li ; Di Shi ; Sharma, Ratnesh

  • Author_Institution
    Univ. of Tennessee, Knoxville, TN, USA
  • fYear
    2015
  • fDate
    18-20 Feb. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper proposes a passive islanding detection technique for microgrid. The proposed technique relies on capturing the underlying signatures of a wide variety of system events on critical system parameters through the utilization of pattern recognition tools for islanding detection in a microgrid. The proposed technique is tested on a microgrid model implemented on IEEE 13-node distribution feeder system under a wide variety of system operating states. Results from test case study have been analyzed to evaluate the effectiveness of the proposed method. Case study results indicate that the proposed method can detect islanding events with high accuracy and reliability.
  • Keywords
    decision trees; distributed power generation; pattern recognition; power distribution faults; IEEE 13-node distribution feeder system; decision tree based approach; microgrid islanding detection; passive islanding detection technique; pattern recognition tools utilization; system operating states; Accuracy; Decision trees; Feature extraction; Load modeling; Mathematical model; Microgrids; Training; Distributed generation; decision tree; islanding detection; microgrids;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Smart Grid Technologies Conference (ISGT), 2015 IEEE Power & Energy Society
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/ISGT.2015.7131809
  • Filename
    7131809